Xearno Tools

Runway & Burn

runway

Read-only

How many months of cash remain, and when to start raising. Computes runway from cash and net burn, optionally with burn trending up or down monthly, and reads the result against fundraising realities: raises take 3–6 months, and 18–24 months post-raise is the norm.

Input Schema

TableJSON Schema

Name	Required	Description
`burn`	No	Net monthly burn Expenses minus revenue. Use the average of the last 3 months.
`cash`	No	Cash in bank
`burnChange`	No	Burn change / month (%) Positive if burn is growing (hiring), negative if revenue is catching up.

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description accurately reflects the read-only nature (readOnlyHint: true) by stating it 'computes' and 'reads' results. It adds behavioral context like burn trending and fundraising realities. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, highly concise, and front-loaded with the primary purpose. Every word contributes meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with no output schema, the description adequately explains the return concept (months of cash, when to raise). It could be improved by specifying output format, but it is sufficient given tool complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Parameter descriptions in the schema are detailed (100% coverage). The tool description adds minimal new semantic information beyond summarizing the parameters' role in the overall calculation. Baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool computes runway from cash and burn, and reads results against fundraising timelines. It uses specific verbs ('computes', 'reads') and resources ('months of cash', 'raise time'), and distinguishes itself from siblings like 'quit_runway' by focusing on startup fundraising.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context on when to use it (runway calculation with fundraising benchmarks) but does not explicitly exclude alternatives or mention when not to use it. The fundraising timeline provides implicit guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0

Disambiguation4/5

Each tool targets a distinct niche (e.g., specific country tax rules, loan types, or legal calculations), with detailed descriptions that clarify boundaries. However, the large number of tools (66) could cause some confusion for an agent trying to select the right one for a general query, especially when multiple tools relate to the same country.

Naming Consistency4/5

Tool names follow a mostly predictable pattern: lowercase words separated by underscores, often starting with a country name (e.g., 'uk_stamp_duty_sdlt') or a topic (e.g., 'compound_growth'). There are minor deviations, such as abbreviations ('npv_irr', 'sip') and varying use of verbs, but overall the naming is clear and consistent.

Tool Count3/5

At 66 tools, the server is unusually large and covers an extensive range of financial and legal calculators. While each tool justifies its existence, the count exceeds the typical well-scoped range (3–15), making the server feel bloated. A more modular design might improve coherence.

Completeness4/5

The tool set covers a wide array of domains: personal income taxes, property taxes, loan calculations, investment returns, and specific country regulations. Minor gaps exist (e.g., missing tools for corporate taxes, general retirement planning, or insurance), but the overall coverage is thorough and addresses many niche scenarios that general AI handles poorly.

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